Gene Expression Analysis Gabor T. Marth Department of Biology, Boston College BI420 Introduction to Bioinformatics Gene expression Why study gene expression? at different developmental stages? in cells of different tissues? at different time points in the same cell? cells under different environmental conditions? between normal and cancerous cells? Which genes are active What are expression microarrays? Expression microarrays physical appearance Microarray construction cDNA preparation Expression assay Expression microarray movieDNA microarray chip animation: Chip readout absolute expression and ratio Chip readout relative transcription Chip readout example Time course experiments Experiment: measuring gene expression as oxygen gets depleted in yeast grown in a closed container Time course data Data analysis normalization balance fluorescent intensities of two dyes adjust for differences in experimental conditions Normalization Log2 transformation Double or half expression now has the same magnitude Clustering intro Why: if the expression pattern for gene B is similar to gene A, maybe they are involved in the same or related pathway How: Re-order expression vectors in the data set so that similar patterns are together Clustering numerical Clustering visual Hierarchical clustering: pair-wise similarity Hierarchical clustering: cluster construction Clustering large example Next two classes Chapter 7. Chapter 8. Application of microarrays: classification of cancers Microarrays to detect genome copy # Protein identification Protein separation by 2D gel eletrophoresis Protein identification mass spectrometry Protein function identification protein chips: identification of proteins that bind specific chemicals Thanks Olga Troyanskaya, Ph.D. Department of Computer Science Lewis-Sigler Institute for Integrative Genomics Princeton University Expression informatics slides courtesy of: